Hello,
It's straight forward to see how the HR's are calculated using the coefficients displayed in the HR table, but, I am trying to figure out how the coefficients are determined (especially the one highlighted in blue below) when using restricted cubic splines in calculating the HR's. A mathematical notation/equation using the ML estimates below when I=0.3 would be great. Or, if someone can point me in the direction of how the SAS output correlates with the math behind it, that would be great!
1. Variable I has a range (0.05 - 0.729)
2. Treatments A and B (2 groups)
3. using 3 equally spaced knots
/*Code*/
proc phreg data = dataset outest=RegParms;
effect I_RCS = spline(I / basis=tpf(noint) NATURALCUBIC details knotmethod=equal(3));
class Treatment(ref='B') Gender(ref='Female');
model T*Status(0, 2, 3) = I_RCS Treatment I_RCS*Treatment Gender Age Score1 Score2 / rl;
hazardratio Treatment / at(I=0.3 0.6) e;
run;
/*SAS Output*/
Knots for Spline Effect |
|
Knot Number |
Frailty |
1 |
0.22297 |
2 |
0.39189 |
3 |
0.56081 |
Basis Details for Spline Effect |
||
Column |
Power |
Break Knot |
1 |
1 |
|
2 |
3 |
0.22297 |
Analysis of Maximum Likelihood Estimates |
|||||||||||
Parameter |
|
|
DF |
Parameter |
Standard |
Chi-Square |
Pr > ChiSq |
Hazard |
95% Hazard Ratio Confidence |
Label |
|
I_RCS |
1 |
|
1 |
-1.34409 |
1.86171 |
0.5212 |
0.4703 |
. |
. |
. |
I_RCS 1 |
I_RCS |
2 |
|
1 |
16.14923 |
7.64104 |
4.4668 |
0.0346 |
. |
. |
. |
I_RCS 2 |
Treatment |
A |
|
1 |
-1.80983 |
0.93087 |
3.7801 |
0.0519 |
. |
. |
. |
Treatment Group A |
I_RCS*Treatment |
1 |
A |
1 |
3.47685 |
3.29380 |
1.1142 |
0.2912 |
. |
. |
. |
I_RCS 1 * Treatment Group A |
I_RCS*Treatment |
2 |
A |
1 |
-15.76844 |
14.59523 |
1.1672 |
0.2800 |
. |
. |
. |
I_RCS 2 * Treatment Group A |
Gender |
Male |
|
1 |
0.12607 |
0.23512 |
0.2875 |
0.5918 |
1.134 |
0.716 |
1.798 |
Gender Male |
Age |
|
|
1 |
0.01625 |
0.01025 |
2.5147 |
0.1128 |
1.016 |
0.996 |
1.037 |
Age |
Score1 |
|
|
1 |
0.01209 |
0.00804 |
2.2624 |
0.1325 |
1.012 |
0.996 |
1.028 |
Score1 |
Score2 |
|
|
1 |
-0.0004364 |
0.00613 |
0.0051 |
0.9432 |
1.000 |
0.988 |
1.012 |
Score2 |
Hazard Ratios for Treatment Group |
||||||||||||
Description |
I_RCS1 Coefficient |
I_RCS2 Coefficient |
TrtA Coefficient |
I_RCS1TrtA Coefficient |
I_RCS2TrtA Coefficient |
GENDERMale Coefficient |
Age Coefficient |
Score1 Coefficient |
Score2 Coefficient |
Point Estimate |
95% Wald Confidence Limits |
|
Trt A vs B At I=0.3 |
0 |
0 |
1.000000 |
0.300000 |
0.001353 |
0 |
0 |
0 |
0 |
0.455 |
0.280 |
0.739 |
Trt A vs B At I=0.6 |
0 |
0 |
1.000000 |
0.600000 |
0.105460 |
0 |
0 |
0 |
0 |
0.250 |
0.057 |
1.088 |
Yes. Unfortunately, the examples don't cover restricted cubic splines and how the coefficients in this specific scenario are calculated.
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